Coordinated Regulation of Two Independent Cell-Cell Signaling Systems and Swarmer Differentiation in<i>Salmonella enterica</i>Serovar Typhimurium
Bibliographic record
Abstract
Almost all members of the genus Salmonella differentiate and migrate on semisolid surfaces in a coordinated population behavior known as swarming. Important virulence determinants are coupled to swarmer differentiation in several other pathogenic organisms, collectively suggesting that conditions that trigger swarming in the laboratory may fortuitously promote the cells to enter a robust physiological state relevant to the host environment. Here, we present evidence that expression of two independent cell-cell signaling systems are also coupled to swarmer differentiation in S. enterica serovar Typhimurium. Expression of both pfs and sdiA genes was up-regulated in the actively migrating swarmers compared to their vegetative counterparts propagated in broth or spread plated on the surface of swim, swarm, and solid media. Accordingly, swarmers produced elevated levels of a universally recognized signaling molecule, autoinducer-2, and exhibited increased sensitivity to N-acyl homoserine lactones (AHLs), signaling molecules that Salmonella does not produce. Expression of the rck operon was concomitantly up-regulated in the swarmers in an SdiA-dependent manner only in the presence of exogenous AHLs. In addition to the previously reported adaptive antibiotic resistance phenotype and global shift in metabolism, this work presents another component of the physiological changes that are specifically associated with swarmer differentiation in serovar Typhimurium and not simply due to growth on a surface.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".